title: A knowledge-based architecture for protein sequence analysis and structure prediction.
abstract: Methods for analyzing the amino-acid sequence of a protein for the purposes of predicting its three-dimensional structure were systematically analyzed using knowledge engineering techniques. The resulting entities (data) and relations (processing methods and constraints) have been represented within a generalized dependency network consisting of 29 nodes and over 100 links. It is argued that such a representation meets the requirements of knowledge-based systems in molecular biology. This network is used as the architecture for a prototype knowledge-based system that simulates logically the processes used in protein structure prediction. Although developed specifically for applications in protein structure prediction, the network architecture provides a strategy for tackling the general problem of orchestrating and integrating the diverse sources of knowledge that are characteristic of many areas of science.
authors.affiliation: Biomedical Computing Unit, Imperial Cancer Research Fund, London, England.
authors.forename: D A
authors.initials: DA
authors.lastname: Clark
authors.forename: G J
authors.initials: GJ
authors.lastname: Barton
authors.forename: C J
authors.initials: CJ
authors.lastname: Rawlings
mesh_terms: D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D014367:Tryptophan Synthase / Q000737:chemistry
chemical_list: D011506:Proteins; D014367:Tryptophan Synthase